Earth Data Science Courses & Workshops

Learn how you can integrate earth science understanding and data science skills to better understand Earth by working through free, self-paced courses online. In the Earth Analytics course, explore how the R programming language and R Markdown is used to work with time series, GIS, remote sensing and social media data. No previous programming experience is required! Stay tuned for a second course build in Python using all open source tools!

Current Courses

Earth Data Science Course Modules

Want to improve your earth data science skills? Complete a set of short, self-paced technical lessons that together create full courses. Following the materials available online for each module, you will learn how to perform a specific workflow using a specific tool that is commonly used in the earth data science field.

This teaching module is a part of the earth-analytics-python course. Last taught: 04 Oct 2018

In this module, you will learn about how scientists study the impacts of wildfire using field surveys and remote sensing. You will also learn about the Cold Springs wildfire, which burned 528 acres near Nederland,... read more.Last updated: 02 Jan 2019

This teaching module is a part of the earth-analytics-bootcamp course. Last taught: 17 Jul 2018

This tutorial helps you get started with open reproducible science and introduces you to tools used in open reproducible science workflows including Bash/Shell, Git and Github.com, and Python in Jupyter Notebook. read more.Last updated: 10 Sep 2018

This teaching module is a part of the earth-analytics-python course. Last taught: 05 Feb 2018

This module explores the use of social media data - specifically Twitter data to better understand the social impacts and perceptions of natural disturbances and other events. Working with social media requires the use of... read more.Last updated: 02 Jan 2019

This teaching module is a part of the earth-analytics-python course. Last taught: 05 Feb 2018

In this module, you learn various ways to access, download and work with data programmatically. These methods include downloading text files directly from a website onto your computer and into Python, reading in data stored... read more.Last updated: 02 Jan 2019

This teaching module is a part of the earth-analytics-python course. Last taught: 05 Feb 2018

This tutorial covers working with spatial data in vector format in Python. You will learn how to import, manipulate and map shapefile data in python. Finally you will learn how to reproject vector data into... read more.Last updated: 08 Oct 2018

This teaching module is a part of the earth-analytics-python course. Last taught: 05 Feb 2018

This module introduces the Python scientific programming language. You will work with precipitation and stream discharge data for Boulder County to better understand the Python syntax, various data types and data import and plotting. read more.Last updated: 08 Oct 2018

This teaching module is a part of the earth-analytics-python course. Last taught: 05 Feb 2018

This lesson series covers working with time series data in Python. You will learn how to handle date fields in Python to create custom plots of time series data using matplotlib. read more.Last updated: 08 Oct 2018

This teaching module is a part of the earth-analytics-python course. Last taught: 05 Feb 2018

This module introduces the raster spatial data format as it relates to working with lidar data in Python. Learn how to to open, crop and classify raster data in Python. read more.Last updated: 30 Oct 2018

This teaching module is a part of the earth-analytics-python course. Last taught: 05 Feb 2018

This module uses time series data to explore the impacts of a flood. Learn how to use Google Earth imagery, NOAA precipitation data and USGS stream flow data to explore the 2013 Colorado floods. read more.Last updated: 25 Sep 2018

This teaching module is a part of the earth-analytics-python course. Last taught: 05 Feb 2018

In this module you will learn about the causes and effects of floods as seen during the 2013 Colorado floods. You will learn how streamflow, precipitation, drought, and remote sensing data are used to better... read more.Last updated: 08 Oct 2018

This teaching module is a part of the earth-analytics course. Last taught: 19 Apr 2017

This module explores the use of social media data - specifically Twitter data to better understand the social impacts and perceptions of natural disturbances and other events. Working with social media requires the use of... read more.Last updated: 10 Jan 2018

This teaching module is a part of the earth-analytics course. Last taught: 05 Apr 2017

In this module, you learn various ways to access, download and work with data programmatically. These methods include downloading text files directly from a website onto your computer and into R, reading in data stored... read more.Last updated: 10 Jan 2018

This teaching module is a part of the earth-analytics course. Last taught: 08 Mar 2017

This module will overview the basic principles of DRY - don't repeat yourself. It will then walk you through incorporating functions into your scientific programming to increase efficiency, clarity, and readability. read more.Last updated: 10 Jan 2018

This teaching module is a part of the earth-analytics course. Last taught: 01 Mar 2017

This tutorial set covers some basic things you can do to refine your plots in Rmarkdown document. It covers plotting in grids, adding titles to plotRGB() plots and refining the width and height of plots... read more.Last updated: 10 Jan 2018

This teaching module is a part of the earth-analytics course. Last taught: 22 Feb 2017

In this module, you will learn how to use multispectral imagery, a type of remote sensing data, to better understand changes in the landscape and how to calculate NDVI using various multispectral datasets You will... read more.Last updated: 10 Jan 2018

This teaching module is a part of the earth-analytics course. Last taught: 15 Feb 2017

In this module, you will learn the concept of uncertainty as it relates to both remote sensing and other data. You will also explore some metadata to learn how to understand more about your data.... read more.Last updated: 10 Jan 2018

This teaching module is a part of the earth-analytics course. Last taught: 01 Feb 2017

This module introduces the raster spatial data format as it relates to working with lidar data in R. You will learn how to open, crop and classify raster data in R. Also you will learn... read more.Last updated: 30 Jul 2018

This teaching module is a part of the earth-analytics course. Last taught: 25 Jan 2017

This module introduces the R scientific programming language. You will work with precipitation and stream discharge data for Boulder County to better understand the R syntax, various data types and data import and plotting. read more.Last updated: 10 Jan 2018

This teaching module is a part of the earth-analytics course. Last taught: 25 Jan 2017

This module covers how to write easier to read, clean code. Further is covers some basic approaches to getting help when working in R. Finally it reviews how to install QGIS - a free and... read more.Last updated: 10 Jan 2018

This teaching module is a part of the earth-analytics course. Last taught: 06 Dec 2016

This module uses time series data to explore the impacts of a flood. Learn how to use Google Earth imagery, NOAA precipitation data and USGS stream flow data to explore the 2013 Colorado floods. read more.Last updated: 10 Jan 2018

This teaching module is a part of the earth-analytics course. Last taught: 06 Dec 2016

This module reviews how to use R Markdown and knitr to create and publish dynamic reports that both link analysis, results and documentation and can be easily updated as data and methods are modified /... read more.Last updated: 10 Jan 2018

This teaching module is a part of the earth-analytics-python course. Last taught: 06 Dec 2016

In this module, we will discuss the concept of uncertainty as it relates to both remote sensing and other data. We will also explore some metadata to learn how to understand more about our data.... read more.Last updated: 08 Oct 2018